Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations536634
Missing cells3454897
Missing cells (%)35.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory73.7 MiB
Average record size in memory144.0 B

Variable types

Numeric13
DateTime1
Boolean3
Categorical1

Alerts

IsHoliday_x is highly overall correlated with IsHoliday_yHigh correlation
IsHoliday_y is highly overall correlated with IsHoliday_xHigh correlation
MarkDown1 is highly overall correlated with MarkDown4 and 1 other fieldsHigh correlation
MarkDown4 is highly overall correlated with MarkDown1High correlation
MarkDown5 is highly overall correlated with MarkDown1 and 1 other fieldsHigh correlation
Size is highly overall correlated with MarkDown5 and 1 other fieldsHigh correlation
Store is highly overall correlated with TypeHigh correlation
Type is highly overall correlated with Size and 1 other fieldsHigh correlation
IsHoliday_x is highly imbalanced (63.3%) Imbalance
IsHoliday_y is highly imbalanced (63.3%) Imbalance
IsHoliday is highly imbalanced (60.6%) Imbalance
Weekly_Sales has 115064 (21.4%) missing values Missing
IsHoliday_x has 115064 (21.4%) missing values Missing
Temperature has 115064 (21.4%) missing values Missing
Fuel_Price has 115064 (21.4%) missing values Missing
MarkDown1 has 385953 (71.9%) missing values Missing
MarkDown2 has 425386 (79.3%) missing values Missing
MarkDown3 has 399543 (74.5%) missing values Missing
MarkDown4 has 401667 (74.8%) missing values Missing
MarkDown5 has 385202 (71.8%) missing values Missing
CPI has 115064 (21.4%) missing values Missing
Unemployment has 115064 (21.4%) missing values Missing
IsHoliday_y has 115064 (21.4%) missing values Missing
Type has 115064 (21.4%) missing values Missing
Size has 115064 (21.4%) missing values Missing
IsHoliday has 421570 (78.6%) missing values Missing

Reproduction

Analysis started2025-02-24 22:12:05.726242
Analysis finished2025-02-24 22:13:16.957604
Duration1 minute and 11.23 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Store
Real number (ℝ)

High correlation 

Distinct45
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.208621
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:17.072477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median22
Q333
95-th percentile43
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation12.79058
Coefficient of variation (CV)0.57592862
Kurtosis-1.1472033
Mean22.208621
Median Absolute Deviation (MAD)11
Skewness0.077554812
Sum11917901
Variance163.59895
MonotonicityIncreasing
2025-02-24T22:13:17.267797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
13 13310
 
2.5%
10 13097
 
2.4%
4 13075
 
2.4%
2 13035
 
2.4%
1 13027
 
2.4%
24 13018
 
2.4%
27 13016
 
2.4%
6 12999
 
2.4%
34 12991
 
2.4%
20 12988
 
2.4%
Other values (35) 406078
75.7%
ValueCountFrequency (%)
1 13027
2.4%
2 13035
2.4%
3 11509
2.1%
4 13075
2.4%
5 11446
2.1%
6 12999
2.4%
7 12431
2.3%
8 12594
2.3%
9 11302
2.1%
10 13097
2.4%
ValueCountFrequency (%)
45 12263
2.3%
44 9241
1.7%
43 8614
1.6%
42 8915
1.7%
41 12842
2.4%
40 12755
2.4%
39 12582
2.3%
38 9349
1.7%
37 9219
1.7%
36 7940
1.5%

Dept
Real number (ℝ)

Distinct81
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.277301
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:17.480172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q118
median37
Q374
95-th percentile95
Maximum99
Range98
Interquartile range (IQR)56

Descriptive statistics

Standard deviation30.527358
Coefficient of variation (CV)0.68945843
Kurtosis-1.2174062
Mean44.277301
Median Absolute Deviation (MAD)23
Skewness0.35914961
Sum23760705
Variance931.9196
MonotonicityNot monotonic
2025-02-24T22:13:17.736109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 8190
 
1.5%
16 8190
 
1.5%
92 8190
 
1.5%
38 8190
 
1.5%
40 8190
 
1.5%
2 8190
 
1.5%
82 8190
 
1.5%
46 8190
 
1.5%
95 8190
 
1.5%
81 8190
 
1.5%
Other values (71) 454734
84.7%
ValueCountFrequency (%)
1 8190
1.5%
2 8190
1.5%
3 8190
1.5%
4 8190
1.5%
5 8085
1.5%
6 7563
1.4%
7 8190
1.5%
8 8190
1.5%
9 8108
1.5%
10 8190
1.5%
ValueCountFrequency (%)
99 1475
 
0.3%
98 7468
1.4%
97 7994
1.5%
96 6204
1.2%
95 8190
1.5%
94 7149
1.3%
93 7551
1.4%
92 8190
1.5%
91 8190
1.5%
90 8190
1.5%

Date
Date

Distinct182
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.1 MiB
Minimum2010-02-05 00:00:00
Maximum2013-07-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-24T22:13:17.967025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:18.220236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Weekly_Sales
Real number (ℝ)

Missing 

Distinct359464
Distinct (%)85.3%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean15981.258
Minimum-4988.94
Maximum693099.36
Zeros73
Zeros (%)< 0.1%
Negative1285
Negative (%)0.2%
Memory size4.1 MiB
2025-02-24T22:13:18.454103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-4988.94
5-th percentile59.9745
Q12079.65
median7612.03
Q320205.853
95-th percentile61201.951
Maximum693099.36
Range698088.3
Interquartile range (IQR)18126.202

Descriptive statistics

Standard deviation22711.184
Coefficient of variation (CV)1.4211136
Kurtosis21.49129
Mean15981.258
Median Absolute Deviation (MAD)6747.645
Skewness3.2620082
Sum6.737219 × 109
Variance5.1579786 × 108
MonotonicityNot monotonic
2025-02-24T22:13:18.688526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 353
 
0.1%
5 289
 
0.1%
20 232
 
< 0.1%
15 215
 
< 0.1%
12 175
 
< 0.1%
1 169
 
< 0.1%
10.47 167
 
< 0.1%
11.97 154
 
< 0.1%
2 148
 
< 0.1%
7 146
 
< 0.1%
Other values (359454) 419522
78.2%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
-4988.94 1
 
< 0.1%
-3924 1
 
< 0.1%
-1750 1
 
< 0.1%
-1699 1
 
< 0.1%
-1321.48 1
 
< 0.1%
-1098 3
< 0.1%
-1008.96 1
 
< 0.1%
-898 1
 
< 0.1%
-863 1
 
< 0.1%
-798 4
< 0.1%
ValueCountFrequency (%)
693099.36 1
< 0.1%
649770.18 1
< 0.1%
630999.19 1
< 0.1%
627962.93 1
< 0.1%
474330.1 1
< 0.1%
422306.25 1
< 0.1%
420586.57 1
< 0.1%
406988.63 1
< 0.1%
404245.03 1
< 0.1%
393705.2 1
< 0.1%

IsHoliday_x
Boolean

High correlation  Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing115064
Missing (%)21.4%
Memory size4.1 MiB
False
391909 
True
 
29661
(Missing)
115064 
ValueCountFrequency (%)
False 391909
73.0%
True 29661
 
5.5%
(Missing) 115064
 
21.4%
2025-02-24T22:13:18.823619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Temperature
Real number (ℝ)

Missing 

Distinct3528
Distinct (%)0.8%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean60.090059
Minimum-2.06
Maximum100.14
Zeros0
Zeros (%)0.0%
Negative69
Negative (%)< 0.1%
Memory size4.1 MiB
2025-02-24T22:13:18.985526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.06
5-th percentile27.31
Q146.68
median62.09
Q374.28
95-th percentile87.27
Maximum100.14
Range102.2
Interquartile range (IQR)27.6

Descriptive statistics

Standard deviation18.447931
Coefficient of variation (CV)0.30700471
Kurtosis-0.63592198
Mean60.090059
Median Absolute Deviation (MAD)13.63
Skewness-0.32140415
Sum25332166
Variance340.32616
MonotonicityNot monotonic
2025-02-24T22:13:19.209164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.43 709
 
0.1%
67.87 646
 
0.1%
72.62 594
 
0.1%
76.67 583
 
0.1%
70.28 563
 
0.1%
76.03 555
 
0.1%
50.56 544
 
0.1%
64.05 542
 
0.1%
64.21 519
 
0.1%
50.81 487
 
0.1%
Other values (3518) 415828
77.5%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
-2.06 69
< 0.1%
5.54 68
< 0.1%
6.23 69
< 0.1%
7.46 69
< 0.1%
9.51 70
< 0.1%
9.55 69
< 0.1%
10.09 66
< 0.1%
10.11 68
< 0.1%
10.24 69
< 0.1%
10.53 72
< 0.1%
ValueCountFrequency (%)
100.14 44
 
< 0.1%
100.07 46
 
< 0.1%
99.66 48
 
< 0.1%
99.22 185
< 0.1%
99.2 46
 
< 0.1%
98.43 43
 
< 0.1%
98.15 47
 
< 0.1%
97.66 42
 
< 0.1%
97.6 48
 
< 0.1%
97.18 187
< 0.1%

Fuel_Price
Real number (ℝ)

Missing 

Distinct892
Distinct (%)0.2%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean3.3610265
Minimum2.472
Maximum4.468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:19.404737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.472
5-th percentile2.653
Q12.933
median3.452
Q33.738
95-th percentile4.029
Maximum4.468
Range1.996
Interquartile range (IQR)0.805

Descriptive statistics

Standard deviation0.45851454
Coefficient of variation (CV)0.13642098
Kurtosis-1.1854045
Mean3.3610265
Median Absolute Deviation (MAD)0.375
Skewness-0.1049015
Sum1416908
Variance0.21023558
MonotonicityNot monotonic
2025-02-24T22:13:19.633755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.638 2548
 
0.5%
3.63 2164
 
0.4%
2.771 1917
 
0.4%
3.891 1856
 
0.3%
3.594 1796
 
0.3%
3.524 1793
 
0.3%
3.523 1792
 
0.3%
2.72 1790
 
0.3%
3.666 1778
 
0.3%
2.78 1656
 
0.3%
Other values (882) 402480
75.0%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
2.472 38
 
< 0.1%
2.513 45
 
< 0.1%
2.514 906
0.2%
2.52 39
 
< 0.1%
2.533 42
 
< 0.1%
2.539 37
 
< 0.1%
2.54 147
 
< 0.1%
2.542 45
 
< 0.1%
2.545 38
 
< 0.1%
2.548 902
0.2%
ValueCountFrequency (%)
4.468 368
0.1%
4.449 358
0.1%
4.308 168
< 0.1%
4.301 360
0.1%
4.294 363
0.1%
4.293 192
< 0.1%
4.288 172
< 0.1%
4.282 173
< 0.1%
4.277 357
0.1%
4.273 366
0.1%

MarkDown1
Real number (ℝ)

High correlation  Missing 

Distinct2277
Distinct (%)1.5%
Missing385953
Missing (%)71.9%
Infinite0
Infinite (%)0.0%
Mean7246.4202
Minimum0.27
Maximum88646.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:19.861418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile149.19
Q12240.27
median5347.45
Q39210.9
95-th percentile21801.35
Maximum88646.76
Range88646.49
Interquartile range (IQR)6970.63

Descriptive statistics

Standard deviation8291.2213
Coefficient of variation (CV)1.1441817
Kurtosis17.606263
Mean7246.4202
Median Absolute Deviation (MAD)3430.74
Skewness3.3418447
Sum1.0918978 × 109
Variance68744351
MonotonicityNot monotonic
2025-02-24T22:13:20.055234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5 102
 
< 0.1%
460.73 102
 
< 0.1%
175.64 93
 
< 0.1%
1282.42 75
 
< 0.1%
9264.48 75
 
< 0.1%
686.24 75
 
< 0.1%
5924.71 75
 
< 0.1%
1483.17 75
 
< 0.1%
3124.45 74
 
< 0.1%
6809.96 74
 
< 0.1%
Other values (2267) 149861
 
27.9%
(Missing) 385953
71.9%
ValueCountFrequency (%)
0.27 51
< 0.1%
0.5 49
< 0.1%
1.5 102
< 0.1%
1.94 50
< 0.1%
2.12 52
< 0.1%
2.4 49
< 0.1%
2.42 50
< 0.1%
2.43 51
< 0.1%
2.8 50
< 0.1%
2.91 51
< 0.1%
ValueCountFrequency (%)
88646.76 68
< 0.1%
78124.5 70
< 0.1%
75149.79 73
< 0.1%
65021.23 73
< 0.1%
62567.6 66
< 0.1%
62172.73 72
< 0.1%
60740.64 70
< 0.1%
60394.73 72
< 0.1%
58928.52 72
< 0.1%
56917.7 71
< 0.1%

MarkDown2
Real number (ℝ)

Missing 

Distinct1499
Distinct (%)1.3%
Missing425386
Missing (%)79.3%
Infinite0
Infinite (%)0.0%
Mean3334.6286
Minimum-265.76
Maximum104519.54
Zeros207
Zeros (%)< 0.1%
Negative1311
Negative (%)0.2%
Memory size4.1 MiB
2025-02-24T22:13:20.291024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-265.76
5-th percentile1.95
Q141.6
median192
Q31926.94
95-th percentile16497.47
Maximum104519.54
Range104785.3
Interquartile range (IQR)1885.34

Descriptive statistics

Standard deviation9475.3573
Coefficient of variation (CV)2.841503
Kurtosis37.589561
Mean3334.6286
Median Absolute Deviation (MAD)184.73
Skewness5.4412612
Sum3.7097076 × 108
Variance89782396
MonotonicityNot monotonic
2025-02-24T22:13:20.608080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.91 539
 
0.1%
3 493
 
0.1%
0.5 485
 
0.1%
1.5 471
 
0.1%
4 367
 
0.1%
6 365
 
0.1%
7.64 354
 
0.1%
3.82 353
 
0.1%
19 345
 
0.1%
5.73 345
 
0.1%
Other values (1489) 107131
 
20.0%
(Missing) 425386
79.3%
ValueCountFrequency (%)
-265.76 71
< 0.1%
-192 72
< 0.1%
-20 72
< 0.1%
-10.98 60
< 0.1%
-10.5 143
< 0.1%
-9.98 68
< 0.1%
-9.94 62
< 0.1%
-7.6 69
< 0.1%
-7.01 69
< 0.1%
-6.69 69
< 0.1%
ValueCountFrequency (%)
104519.54 72
< 0.1%
97740.99 73
< 0.1%
92523.94 73
< 0.1%
89121.94 74
< 0.1%
82881.16 73
< 0.1%
72413.71 72
< 0.1%
70574.85 71
< 0.1%
58804.91 69
< 0.1%
58046.41 71
< 0.1%
56106.2 72
< 0.1%

MarkDown3
Real number (ℝ)

Missing 

Distinct1662
Distinct (%)1.2%
Missing399543
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean1439.4214
Minimum-29.1
Maximum141630.61
Zeros67
Zeros (%)< 0.1%
Negative257
Negative (%)< 0.1%
Memory size4.1 MiB
2025-02-24T22:13:20.932979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-29.1
5-th percentile0.65
Q15.08
median24.6
Q3103.99
95-th percentile1059.9
Maximum141630.61
Range141659.71
Interquartile range (IQR)98.91

Descriptive statistics

Standard deviation9623.0783
Coefficient of variation (CV)6.6853796
Kurtosis77.687772
Mean1439.4214
Median Absolute Deviation (MAD)22.6
Skewness8.399453
Sum1.9733172 × 108
Variance92603636
MonotonicityNot monotonic
2025-02-24T22:13:21.366098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 754
 
0.1%
6 710
 
0.1%
2 660
 
0.1%
1 611
 
0.1%
0.22 487
 
0.1%
0.5 463
 
0.1%
0.01 444
 
0.1%
4 439
 
0.1%
3.2 379
 
0.1%
1.98 363
 
0.1%
Other values (1652) 131781
 
24.6%
(Missing) 399543
74.5%
ValueCountFrequency (%)
-29.1 72
 
< 0.1%
-1 70
 
< 0.1%
-0.87 46
 
< 0.1%
-0.2 69
 
< 0.1%
0 67
 
< 0.1%
0.01 444
0.1%
0.02 124
 
< 0.1%
0.04 241
< 0.1%
0.05 71
 
< 0.1%
0.06 205
< 0.1%
ValueCountFrequency (%)
141630.61 74
< 0.1%
109030.75 75
< 0.1%
103991.94 72
< 0.1%
101378.79 73
< 0.1%
89402.64 71
< 0.1%
88805.58 72
< 0.1%
83340.33 74
< 0.1%
83192.81 74
< 0.1%
79621.2 72
< 0.1%
77451.26 73
< 0.1%

MarkDown4
Real number (ℝ)

High correlation  Missing 

Distinct1944
Distinct (%)1.4%
Missing401667
Missing (%)74.8%
Infinite0
Infinite (%)0.0%
Mean3383.1683
Minimum0.22
Maximum67474.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:21.754791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.22
5-th percentile28.76
Q1504.22
median1481.31
Q33595.04
95-th percentile12645.96
Maximum67474.85
Range67474.63
Interquartile range (IQR)3090.82

Descriptive statistics

Standard deviation6292.384
Coefficient of variation (CV)1.8599087
Kurtosis29.996815
Mean3383.1683
Median Absolute Deviation (MAD)1167.55
Skewness4.8475
Sum4.5661607 × 108
Variance39594097
MonotonicityNot monotonic
2025-02-24T22:13:22.160093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 280
 
0.1%
4 200
 
< 0.1%
2 197
 
< 0.1%
3 146
 
< 0.1%
47 143
 
< 0.1%
67.72 142
 
< 0.1%
657.56 141
 
< 0.1%
17 141
 
< 0.1%
8 140
 
< 0.1%
1330.36 140
 
< 0.1%
Other values (1934) 133297
 
24.8%
(Missing) 401667
74.8%
ValueCountFrequency (%)
0.22 57
 
< 0.1%
0.41 52
 
< 0.1%
0.46 48
 
< 0.1%
0.78 52
 
< 0.1%
0.87 49
 
< 0.1%
0.92 45
 
< 0.1%
1.5 55
 
< 0.1%
1.88 48
 
< 0.1%
1.98 44
 
< 0.1%
2 197
< 0.1%
ValueCountFrequency (%)
67474.85 72
< 0.1%
57817.56 74
< 0.1%
57815.43 68
< 0.1%
53603.99 72
< 0.1%
52739.02 72
< 0.1%
48403.53 70
< 0.1%
48159.86 73
< 0.1%
48086.64 72
< 0.1%
47452.43 73
< 0.1%
46238.28 71
< 0.1%

MarkDown5
Real number (ℝ)

High correlation  Missing 

Distinct2293
Distinct (%)1.5%
Missing385202
Missing (%)71.8%
Infinite0
Infinite (%)0.0%
Mean4628.9751
Minimum135.16
Maximum108519.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:22.491418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum135.16
5-th percentile715.52
Q11878.44
median3359.45
Q35563.8
95-th percentile11269.24
Maximum108519.28
Range108384.12
Interquartile range (IQR)3685.36

Descriptive statistics

Standard deviation5962.8875
Coefficient of variation (CV)1.2881658
Kurtosis107.84927
Mean4628.9751
Median Absolute Deviation (MAD)1702.47
Skewness8.1699095
Sum7.0097495 × 108
Variance35556027
MonotonicityNot monotonic
2025-02-24T22:13:22.903656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2743.18 136
 
< 0.1%
1064.56 120
 
< 0.1%
9083.54 75
 
< 0.1%
3567.03 75
 
< 0.1%
3557.67 75
 
< 0.1%
20371.02 75
 
< 0.1%
4180.29 75
 
< 0.1%
1773.53 74
 
< 0.1%
3932.94 74
 
< 0.1%
4464.45 74
 
< 0.1%
Other values (2283) 150579
 
28.1%
(Missing) 385202
71.8%
ValueCountFrequency (%)
135.16 65
< 0.1%
153.04 47
< 0.1%
153.9 49
< 0.1%
164.08 52
< 0.1%
170.64 69
< 0.1%
171.76 71
< 0.1%
180.07 64
< 0.1%
212.75 50
< 0.1%
224.86 50
< 0.1%
227.12 48
< 0.1%
ValueCountFrequency (%)
108519.28 68
< 0.1%
105223.11 70
< 0.1%
85851.87 68
< 0.1%
63005.58 69
< 0.1%
58068.14 69
< 0.1%
57029.78 68
< 0.1%
53212.72 70
< 0.1%
37581.27 70
< 0.1%
36430.33 71
< 0.1%
36360.42 72
< 0.1%

CPI
Real number (ℝ)

Missing 

Distinct2145
Distinct (%)0.5%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean171.20195
Minimum126.064
Maximum227.23281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:23.235395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum126.064
5-th percentile126.49626
Q1132.02267
median182.31878
Q3212.41699
95-th percentile221.94156
Maximum227.23281
Range101.16881
Interquartile range (IQR)80.394326

Descriptive statistics

Standard deviation39.159276
Coefficient of variation (CV)0.22873149
Kurtosis-1.8297144
Mean171.20195
Median Absolute Deviation (MAD)41.434863
Skewness0.085219285
Sum72173605
Variance1533.4489
MonotonicityNot monotonic
2025-02-24T22:13:23.601157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.8555333 711
 
0.1%
131.1083333 708
 
0.1%
129.8459667 707
 
0.1%
130.6457931 706
 
0.1%
131.0756667 706
 
0.1%
130.3849032 706
 
0.1%
130.683 706
 
0.1%
130.4546207 705
 
0.1%
130.7196333 705
 
0.1%
130.737871 704
 
0.1%
Other values (2135) 414506
77.2%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
126.064 678
0.1%
126.0766452 679
0.1%
126.0854516 675
0.1%
126.0892903 682
0.1%
126.1019355 686
0.1%
126.1069032 681
0.1%
126.1119032 682
0.1%
126.114 687
0.1%
126.1145806 689
0.1%
126.1266 683
0.1%
ValueCountFrequency (%)
227.2328068 63
< 0.1%
227.214288 62
< 0.1%
227.1693919 63
< 0.1%
227.0369359 70
< 0.1%
227.0184166 69
< 0.1%
226.9873637 134
< 0.1%
226.9735448 69
< 0.1%
226.9688442 134
< 0.1%
226.9662325 63
< 0.1%
226.9239785 135
< 0.1%

Unemployment
Real number (ℝ)

Missing 

Distinct349
Distinct (%)0.1%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean7.9602887
Minimum3.879
Maximum14.313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:24.009778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum3.879
5-th percentile5.326
Q16.891
median7.866
Q38.572
95-th percentile12.187
Maximum14.313
Range10.434
Interquartile range (IQR)1.681

Descriptive statistics

Standard deviation1.863296
Coefficient of variation (CV)0.23407393
Kurtosis2.7312166
Mean7.9602887
Median Absolute Deviation (MAD)0.858
Skewness1.1837426
Sum3355818.9
Variance3.4718721
MonotonicityNot monotonic
2025-02-24T22:13:24.434829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.099 5152
 
1.0%
8.163 3636
 
0.7%
7.852 3614
 
0.7%
7.343 3416
 
0.6%
7.057 3414
 
0.6%
7.931 3400
 
0.6%
7.441 3397
 
0.6%
6.565 3370
 
0.6%
8.2 3361
 
0.6%
6.891 3360
 
0.6%
Other values (339) 385450
71.8%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
3.879 287
 
0.1%
4.077 938
0.2%
4.125 1831
0.3%
4.145 562
 
0.1%
4.156 1815
0.3%
4.261 1829
0.3%
4.308 935
0.2%
4.42 1855
0.3%
4.584 1988
0.4%
4.607 935
0.2%
ValueCountFrequency (%)
14.313 2636
0.5%
14.18 2423
0.5%
14.099 2441
0.5%
14.021 2263
0.4%
13.975 1529
0.3%
13.736 2464
0.5%
13.503 2661
0.5%
12.89 2491
0.5%
12.187 2507
0.5%
11.627 2502
0.5%

IsHoliday_y
Boolean

High correlation  Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing115064
Missing (%)21.4%
Memory size4.1 MiB
False
391909 
True
 
29661
(Missing)
115064 
ValueCountFrequency (%)
False 391909
73.0%
True 29661
 
5.5%
(Missing) 115064
 
21.4%
2025-02-24T22:13:24.719790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Type
Categorical

High correlation  Missing 

Distinct3
Distinct (%)< 0.1%
Missing115064
Missing (%)21.4%
Memory size4.1 MiB
A
215478 
B
163495 
C
42597 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters421570
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A 215478
40.2%
B 163495
30.5%
C 42597
 
7.9%
(Missing) 115064
21.4%

Length

2025-02-24T22:13:24.848631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-24T22:13:24.948789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
a 215478
51.1%
b 163495
38.8%
c 42597
 
10.1%

Most occurring characters

ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Size
Real number (ℝ)

High correlation  Missing 

Distinct40
Distinct (%)< 0.1%
Missing115064
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean136727.92
Minimum34875
Maximum219622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-02-24T22:13:25.106092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum34875
5-th percentile39690
Q193638
median140167
Q3202505
95-th percentile206302
Maximum219622
Range184747
Interquartile range (IQR)108867

Descriptive statistics

Standard deviation60980.583
Coefficient of variation (CV)0.44599951
Kurtosis-1.2063459
Mean136727.92
Median Absolute Deviation (MAD)62140
Skewness-0.32584977
Sum5.7640387 × 1010
Variance3.7186315 × 109
MonotonicityNot monotonic
2025-02-24T22:13:25.309117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
39690 20802
 
3.9%
39910 20597
 
3.8%
203819 20376
 
3.8%
219622 10474
 
2.0%
126512 10315
 
1.9%
205863 10272
 
1.9%
151315 10244
 
1.9%
202307 10238
 
1.9%
204184 10225
 
1.9%
158114 10224
 
1.9%
Other values (30) 287803
53.6%
(Missing) 115064
 
21.4%
ValueCountFrequency (%)
34875 8999
1.7%
37392 9036
1.7%
39690 20802
3.9%
39910 20597
3.8%
41062 6751
 
1.3%
42988 7156
 
1.3%
57197 9443
1.8%
70713 9762
1.8%
93188 9864
1.8%
93638 9455
1.8%
ValueCountFrequency (%)
219622 10474
2.0%
207499 10062
1.9%
206302 10113
1.9%
205863 10272
1.9%
204184 10225
1.9%
203819 20376
3.8%
203750 10142
1.9%
203742 10214
1.9%
203007 10202
1.9%
202505 10211
1.9%

IsHoliday
Boolean

Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing421570
Missing (%)78.6%
Memory size4.1 MiB
False
106136 
True
 
8928
(Missing)
421570 
ValueCountFrequency (%)
False 106136
 
19.8%
True 8928
 
1.7%
(Missing) 421570
78.6%
2025-02-24T22:13:25.447050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-02-24T22:13:08.820343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:32.133607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:34.688415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:37.256931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:41.322443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:44.899839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:47.771491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.097673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:52.698789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:57.184876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:59.835124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:02.313238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:05.006602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:09.145956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:32.351364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:34.881520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:37.474587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:41.664953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:45.141201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:47.945375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.283700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:52.984044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:57.374963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.016247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:02.527370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:05.209615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:09.512200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:32.558457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:35.076386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:37.725126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:42.013679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:45.369176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:48.127608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.462633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:53.271267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:57.604987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.198970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:02.739865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:05.420358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:09.856361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:32.780868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:35.281017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:38.022966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:42.238146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:45.627628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:48.303362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.638489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:53.575510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:57.830226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.387044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:02.979395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:05.663764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:10.211658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:32.966228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:35.486151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:38.379090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:42.460579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:45.853526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:48.483361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.801869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:53.849044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:58.012966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.572617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:03.209986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:05.889223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:10.513373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:33.139185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:35.694762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:38.704908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:42.679750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:46.076736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:48.665417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:50.979780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:54.172973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:58.208330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.767729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:03.403605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:06.138981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:10.709153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:33.287580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:35.860204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:39.012396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:43.502357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:46.264175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:48.834195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:51.144486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:54.498600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:58.389348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:00.960010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-02-24T22:12:36.036908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:39.344438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:43.681979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:46.455109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:49.016761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:51.332720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:54.818185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:58.585487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:01.152680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:03.759528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-02-24T22:13:11.093682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:33.668943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:36.214602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:39.661333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:43.862413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:46.660304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-02-24T22:13:03.954453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:07.092312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:11.291763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:33.844494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:36.411097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:39.998898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:44.065581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:46.853934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:49.432614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:51.698621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:56.369577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:59.010985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:01.540268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:04.139501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:07.421029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-02-24T22:12:34.042405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-02-24T22:12:56.978444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:12:59.600821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:02.082929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:04.768705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-24T22:13:08.442633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-02-24T22:13:25.558031image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
CPIDeptFuel_PriceIsHolidayIsHoliday_xIsHoliday_yMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5SizeStoreTemperatureTypeUnemploymentWeekly_Sales
CPI1.000-0.009-0.0410.0000.0120.012-0.017-0.099-0.111-0.0630.021-0.005-0.2300.1730.183-0.383-0.023
Dept-0.0091.0000.0030.0000.0000.0000.0020.0030.0060.0070.0060.0110.0140.0010.0800.006-0.014
Fuel_Price-0.0410.0031.0000.0000.1360.1360.163-0.155-0.2180.073-0.0880.0040.0740.1280.088-0.0600.002
IsHoliday0.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
IsHoliday_x0.0120.0000.1360.0001.0001.0000.0570.3590.4580.1150.0600.0000.0000.1860.0000.0350.031
IsHoliday_y0.0120.0000.1360.0001.0001.0000.0570.3590.4580.1150.0600.0000.0000.1860.0000.0350.031
MarkDown1-0.0170.0020.1630.0000.0570.0571.0000.2060.1540.7590.5080.499-0.2120.0020.1720.0640.192
MarkDown2-0.0990.003-0.1550.0000.3590.3590.2061.0000.0660.1160.1520.1490.009-0.4620.0660.0600.032
MarkDown3-0.1110.006-0.2180.0000.4580.4580.1540.0661.0000.0020.2440.300-0.065-0.2570.0650.0430.135
MarkDown4-0.0630.0070.0730.0000.1150.1150.7590.1160.0021.0000.3800.288-0.0390.1410.0660.0380.112
MarkDown50.0210.006-0.0880.0000.0600.0600.5080.1520.2440.3801.0000.579-0.156-0.0710.094-0.0190.208
Size-0.0050.0110.0040.0000.0000.0000.4990.1490.3000.2880.5791.000-0.160-0.0430.851-0.0660.290
Store-0.2300.0140.0740.0000.0000.000-0.2120.009-0.065-0.039-0.156-0.1601.000-0.0570.5380.295-0.102
Temperature0.1730.0010.1280.0000.1860.1860.002-0.462-0.2570.141-0.071-0.043-0.0571.0000.1230.030-0.020
Type0.1830.0800.0880.0000.0000.0000.1720.0660.0650.0660.0940.8510.5380.1231.0000.1810.089
Unemployment-0.3830.006-0.0600.0000.0350.0350.0640.0600.0430.038-0.019-0.0660.2950.0300.1811.000-0.016
Weekly_Sales-0.023-0.0140.0020.0000.0310.0310.1920.0320.1350.1120.2080.290-0.102-0.0200.089-0.0161.000

Missing values

2025-02-24T22:13:13.329144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-24T22:13:14.279087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-24T22:13:16.249585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

StoreDeptDateWeekly_SalesIsHoliday_xTemperatureFuel_PriceMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5CPIUnemploymentIsHoliday_yTypeSizeIsHoliday
0112010-02-0524924.50False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
1122010-02-0550605.27False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
2132010-02-0513740.12False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
3142010-02-0539954.04False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
4152010-02-0532229.38False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
5162010-02-055749.03False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
6172010-02-0521084.08False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
7182010-02-0540129.01False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
8192010-02-0516930.99False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
91102010-02-0530721.50False42.312.572NaNNaNNaNNaNNaN211.0963588.106FalseA151315.0NaN
StoreDeptDateWeekly_SalesIsHoliday_xTemperatureFuel_PriceMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5CPIUnemploymentIsHoliday_yTypeSizeIsHoliday
53662445852013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53662545872013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53662645902013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53662745912013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53662845922013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53662945932013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53663045942013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53663145952013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53663245972013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse
53663345982013-07-26NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalse